tf.train.slice_input_producer(tensor_list, num_epochs=None, shuffle=True, seed=None, capacity=32, shared_name=None, name=None)

tf.train.slice_input_producer(tensor_list, num_epochs=None, shuffle=True, seed=None, capacity=32, shared_name=None, name=None)

See the guide: Inputs and Readers > Input pipeline

Produces a slice of each Tensor in tensor_list.

Implemented using a Queue -- a QueueRunner for the Queue is added to the current Graph's QUEUE_RUNNER collection.

Args:

  • tensor_list: A list of Tensor objects. Every Tensor in tensor_list must have the same size in the first dimension.
  • num_epochs: An integer (optional). If specified, slice_input_producer produces each slice num_epochs times before generating an OutOfRange error. If not specified, slice_input_producer can cycle through the slices an unlimited number of times.
  • shuffle: Boolean. If true, the integers are randomly shuffled within each epoch.
  • seed: An integer (optional). Seed used if shuffle == True.
  • capacity: An integer. Sets the queue capacity.
  • shared_name: (optional). If set, this queue will be shared under the given name across multiple sessions.
  • name: A name for the operations (optional).

Returns:

A list of tensors, one for each element of tensor_list. If the tensor in tensor_list has shape [N, a, b, .., z], then the corresponding output tensor will have shape [a, b, ..., z].

Raises:

  • ValueError: if slice_input_producer produces nothing from tensor_list.

Defined in tensorflow/python/training/input.py.